Python Basics

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Python Programming Language  
In this article ,Iam going to explain about python language and how it’s contents are working like print(), for,if etc.
But first,we have to understand about python :-
Python programming is one of the famous languages in programming field. Reason is , it is both easy to pick up and has vast capabilities. Python Programming language uses simple object-oriented programming(OOPS) approach and very efficient high-level data structures. 

Python Programming also uses very simple and use small type syntax . If you want a language for application building and scripting in several areas.
One of the key benefits of Python Programming is its interpretive nature. The Python interpreter and standard library are available in binary or source form from the Python website, and can run seamlessly on all major operating systems. Python Programming language is also freely-distributable, and the same site even has tips and other third-party tools, programs, modules and more documentation.

Benefits of Python Programming Language

  • Interpreted language: the language is processed by the interpreter at runtime, like PHP or PERL, so you don’t have to compile the program before execution.
  • Interactive: you can directly interact with the interpreter at the Python for writing your program.
  • Perfect for beginners: for beginner-level programmers, Python is a great choice as it supports the development of applications ranging from games to browsers to text processing.

Where Python Programming start

Python is also one of the best web development languages out there, made by Guido van Rossum at  National Research Institute for Mathematics and Computer Science in the Netherlands in the early 90s. The language borrows heavily from C, C++, SmallTalk, Unix Shell, Modula-3, ABC, Algol-68 and other scripting languages. Rossum continues to direct the language progress, although a core development team at the institute now maintains most of it.

Learning Python Programming Language

English language keywords make up most of the programming in Python. If you master them, you have mastered Python for the most part. It will take time and some practice, and you need to know the basic concepts before you start . So let’s begin :


Python is implicitly and dynamically typed, so you do not have to declare variables. The types are enforced, and the variables are also case sensitive, so var and VAR are treated as two separate variables. If you want to know how any object work, you just need to type the following:

Data types

Let’s move ahead to data types. The data structures in Python are dictionaries, tuples and lists. Sets can be found in the sets library that are available in all versions of Python from 2.5 . Lists are similar to one-dimensional arrays, although you can also have lists of other lists. Dictionaries are essentially associative arrays, or hash tables. Tuples are one-dimensional arrays.

You can use the colon to access array ranges. If you leave the start index empty, the interpreter assumes the first item, so the end index assumes the last item. Negative indexes count from the last item, so -1 is seen as the last item. Here is an example:
In the last line, adding a third parameter will see Python step in the N item increments, instead of one. For instance, in the above sample code, the first item is returned and then the third, so items zero and two in zero-indexing.
Let’s move on to strings. Python strings can either use single or double quotation marks, and you can use quotation marks of one kind in a string using another kind, so the following is valid:
“This is a ‘valid’ string”
Multi-strings are enclosed in single or triple double quotes. Python can support Unicode right from the start, using the following syntax:
u”This is Unicode”
To fill strings with values, you can use the modulo (%) operator and then a tuple. Each % gets replaced with a tuple item from left to right, and you can use dictionary substitutions as well.
strString = """This is a multiline string."""
>>> print ("This %(verb)s a %(noun)s." % {"noun": "test", "verb": "is"}
This is a test.)
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Flow control statements
Python’s flow control statements are ‘while’, ‘for’ and ‘if’. For a switch, you need to use ‘if’. For enumerating through list members, use ‘for’. For obtaining a number list, use range (number). 
Here is the statement syntax:
rangelist = range(10)
print (rangelist)
The ‘def’ keyword is used to declare functions. Optional arguments can be set in the function declaration after mandatory arguments, by assigning them default values. In case of named arguments, the argument name is assigned a value. Functions can return a tuple, and you can effective return a variable.

 Parameters are passed through reference, but tuples, ints, strings and other immutable types are unchangeable because only the memory location of the item is passed. Binding another object to the variable removed the older one and replaces immutable types. Here is an example:
func = lambda x: x + 1
print (func(1))

def p(list, int=2, string="string"):
list.append("new name")
int = 4
return list, int, string
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Python supports a very limited multiple class inheritance.

Private methods and variables can be declared wth the addition of two or more underscores and at most one trailing one. You can also bind names to class instances, like so.
class MyClass(object):
common = 10
def __init__(self):
self.myvariable = 3
defmyfunction(self, arg1, arg2):
return self.myvariable
>>>classinstance = MyClass()
>>>classinstance.myfunction(1, 2)
In Python, Exceptions are handled via try-except blocks [exceptionname]. Here is an example syntax:
def some_function():
10 / 0
except ZeroDivisionError:
print "Oops, invalid."
print ("We're done with that.")
Oops, invalid.
We're done with that.
In Python, external libraries can be used using the keyword import[library]. For individual functions, you can use from [funcname] or [libname] import. Take a look at the following sample syntax:
import random
from time import clock
randomint = random.randint(1, 100)
>>> print (randomint)
 File I/O
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The Python programing language comes with a lot of libraries to begin with. For instance, here is a look at how we convert data structures to strings with the use of the pickle library using file I/O:
import pickle
mylist = ["This", "is", 4, 13327] 
myfile = open(r"C:\\binary.dat", "w")
pickle.dump(mylist, myfile)
myfile = open(r"C:\\text.txt", "w")
myfile = open(r"C:\\text.txt")
>>> print (
# file for reading.
myfile = open(r"C:\\binary.dat")
loadedlist = pickle.load(myfile)
>>> print (loadedlist)
['This', 'is', 4, 13327]

Conditions and variables

Conditions in Python can be changed. For instance, take a look at this condition:
1 < a < 3
This condition checks that a is greater than one and also less than three. You can also use ‘del’ to delete items or variables in arrays. A great way to manipulate and create lists is through list comprehensions, which have an expression and then a ‘for’ clause, followed by a zero or more ‘for’ or ‘if’ clauses. Here is an example:
>>> lst1 = [1, 2, 3] 
>>> lst2 = [3, 4, 5] 
>>> print ([x * y for x in lst1 for y in lst2] [3, 4, 5, 6, 8]) 
>>> print ([x for x in lst1 if 4 > x > 1] [2, 3]) 
>>> any([i % 3 for i in [3, 3, 4 ]])
>>> sum(1 for i in [3, 3, 4] if i == 4)
>>> del lst1[0] 

>>> print (lst1)
[2, 3] 
>>> del lst1
Global variables are called so because they are declared outside functions and are readable without special declarations. However, if you want to write them, you need to declare them at the start of the function with the ‘global’ keyword. Otherwise, Python will bind the object to a new local variable. Take a look at the sample syntax below:
number = 5
def myfunc():
   print (number)
def anotherfunc():
  print (number)
number = 5
def yetanotherfunc():
global number
number = 5


There is a lot to python than what is mentioned above. As always,Python, want  practicing and experimenting. Python has a huge array of libraries and  functionality that you can discover on internet. You can also find some other great books and resources to get more in-depth about Python. From classes and error handling to subsets and more topics could you learn. There will be syntax errors galore, but keep going at it and utilize the excellent Python community and resources available.


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